New technology and data analytics for calf health (PhD)

The Challenge

Calves are the future of any herd - whether beef or dairy - and it is crucial to get the first months of life right. However, research suggests that ~5% of dairy heifers and ~3% of beef (including beef x dairy) calves die in the first three months of life. Farmers are making increasing use of technology, such as automatic calf feeders and accelerometers, to measure activity.

The Project

We can use these technologies to measure behaviours, including feeding behaviours such as drinking speed and lying behaviour. These behaviours change when calves become unwell.My research will investigate whether these changes can be used to accurately detect diseases such as pneumonia and scour early. This will allow earlier treatment and hopefully better outcomes for the calves.

I also plan to explore novel indicators using sensors that would help with disease detection. One area of this I am particularly interested in, is whether saliva can be used to measure dehydration in a calf. If this is possible, then information from a calf’s saliva could be included in disease detection algorithms.

Artificially reared calves in the UK are fed on varying levels of milk replacer, this may have an impact on their health. We know that the behaviour changes calves display when ill can depend on the level of their nutrition. There is also evidence that a calf’s nutrition can affect their immune response to disease. I aim to bring this work together, investigate the effects of different nutrition levels on calf health, behaviour and immune response.

Student

Bethan Riley, SRUC